Currently, the perturbation loss metric assumes that the result is based on classification, so the performance drop is just the difference of output of softmax for a specific class, before and after perturbation.
To use it in other non-classification tasks, one needs to define what does it mean to be performance drop. This should be refactored as a separate function to be injected during the computation of the performance loss.
Currently, the perturbation loss metric assumes that the result is based on classification, so the performance drop is just the difference of output of softmax for a specific class, before and after perturbation.
To use it in other non-classification tasks, one needs to define what does it mean to be performance drop. This should be refactored as a separate function to be injected during the computation of the performance loss.
The default should be classification.